Device and method for interpolating frequency components of signal adaptively

ABSTRACT

A frequency interpolating device for restoring a signal similar to the original signal by creating a suppressed frequency component of a specific frequency band of the original signal, approximately from the input signal having the suppressed frequency component. In the frequency interpolating device, when the suppressed frequency component is artificially created from the input signal and added to the input signal, the additional level is set dynamically and adaptively on the basis of the spectrum pattern of the remaining frequency component of the input signal. This setting of the addition level is done by searching a look-up table which stores data that causes a plurality of reference frequency spectrum patterns to be associated with predetermined addition levels. Moreover, the data stored in the table is created on the basis of the results of either an aural test on a plurality of signal sample sounds or a physical frequency analysis on the massive signal data.

TECHNICAL FIELD

The present invention relates to a frequency interpolating device andmethod for improving the spectrum distribution of a signal having thefrequency components in a particular frequency band being removed orsuppressed, by recovering the frequency components in the particularfrequency band as approximate values and adaptively interpolating theapproximate values into the signal.

BACKGROUND ART

Supply of music and the like is flourishing nowadays by means of datadistribution by MP3 (MPEG1 audio layer 3), FM (Frequency Modulation)broadcasting, voice multiplexing broadcasting and the like. With thesemeans, a data transmission rate (bit/s) changing proportionally with afrequency bandwidth is lowered and the upper frequency limit is loweredby suppressing the high frequency components of a subject audio signalor the like in order to avoid an occupied broad bandwidth andeffectively use radio wave resources. For example, if the upperfrequency limit is lowered by suppressing the frequency components atabout 15 kHz or higher of an audio signal having the upper limitfrequency of 20 kHz, the sampling frequency is only ¾ of the originalsignal frequency so that the data transmission rate can be loweredadvantageously. However, it is obvious that an audio signal withsuppressed high frequency components has a sound quality inferior tothat of the original signal. From this reason, it has been tried torecover approximate suppressed frequency components by some means. Inone approach to recover frequency components, a subject signal isdistorted to obtain a distorted signal, the frequency band components tobe interpolated into the suppressed band are derived from the distortedsignal by using a filter, and the frequency band components are added tothe target signal to reproduce a signal approximated to the originalsignal.

In another approach, voice components containing a pair of a fundamentaltone and a harmonic tone are derived from an original audio signal,harmonic components on the high frequency side are estimated from thebandwidth of the original audio signal, and the estimated harmoniccomponents are extrapolated relative to the original audio signal.

With the former approach, however, since the waveform of an audio signalis distorted by using a limiter circuit or the like to create harmonics,these harmonics are not necessarily approximate values essentiallycontained in the original audio signal.

If the latter approach is applied to an original audio signal whosebandwidth of voices or the like was limited, harmonic components of puresound components cannot be estimated so that extrapolation isimpossible. Similarly, sound components whose harmonic components wereremoved because of a limited bandwidth cannot be estimated andextrapolation is impossible.

In a relatively good approach, a target signal is frequency analyzed,its frequency spectrum pattern is used for estimating the remainingspectrum pattern of suppressed frequency components, and a signalsynthesized from these is added to the target signal. Although thisapproach is excellent in sound quality improvement, there is a practicalproblem. Namely, it is necessary for this approach to use a short timeFourier transform process and a short time inverse Fourier transformprocess which are performed at a high resolution over the broad band ofa subject signal, resulting in a large amount of computation requiredfor digital signal processing. This leads to requirements for anexcessive calculation amount and an excessive circuit scale of a digitalsignal processor (DSP), lowering a practical value.

In a recently devised approach which proposes a frequency interpolatingdevice and method, the remaining band components of a signal whosefrequency components in a particular band were suppressed are derived byusing a band-pass filter or the like, frequency-converted and added tothe suppressed band wherein the addition level is properly determinedfrom the spectrum envelope information of the remaining frequencycomponents.

Generally, the short time frequency spectrum pattern of a signal hascomplicated states and its envelope cannot be said that it changesmonotonously and smoothly. Therefore, if the intensities of suppressedband components are estimated only from the envelope information andinterpolation is performed in a simple manner, a signal not essentiallycontained in the original signal may be added or an interpolation signalat an excessive level may be added. In this case, the sound quality isnot improved but degraded.

The present invention has been made under the above-describedcircumstances, and aims at providing a signal interpolating device andmethod having a high practical value capable of recovering an originalsignal such as an audio signal of high quality from a signal with asuppressed particular frequency band (e.g., high frequency band) of theoriginal signal, providing a very excellent sound quality in terms ofauditory senses, and performing signal processing by relatively smallscale digital computation.

DISCLOSURE OF THE INVENTION

In order to achieve the above objective, a frequency interpolatingdevice of the present invention can create approximate suppressedfrequency components from an input signal with suppressed frequencycomponents of the original signal in a particular frequency band and canrecover auditory characteristics of the original signal. In afundamental operation of generating the suppressed frequency componentsfrom the input signal and adding them to the input signal, the additionlevel is adaptively set in accordance with the spectrum pattern of theremaining frequency components of the input signal.

Setting the addition level is performed by using a look-up table storingdata representative of a correspondence between a plurality of referencefrequency spectrum patterns and their addition levels. This look-uptable is created in accordance with the auditory test results of aplurality of acoustic signal samples or in accordance with the frequencyanalysis results of a plurality of acoustic signal samples.

More specifically, the frequency interpolating device of this inventioncomprises: means for generating an interpolation signal having afrequency component in the suppressed band, from the input signal; meansfor spectrum-analyzing the input signal to derive a spectrum pattern;comparing means for comparing the derived spectrum pattern with aplurality of reference spectrum patterns registered in advance, and inaccordance with a comparison result, selecting an addition level of thecreated interpolation signal relative to the input signal; and means foradding the created interpolation signal to the input signal at theselected addition level. The comparing means includes a search datatable storing data representative of a correspondence between thereference spectrum patterns and the addition levels, the search datatable being created in accordance with an auditory test of a pluralityof acoustic signal samples.

The means for deriving the spectrum pattern of the input signal outputsa code corresponding to the derived spectrum pattern, the comparingmeans is made of a memory storing data representative of acorrespondence between the reference spectrum patterns and the additionlevels, and the code is supplied to the memory as a memory address tooutput the addition level stored at a memory location indicated by thememory address designated by the code.

In the device of the invention, the input signal is typically a digitalaudio signal obtained by sampling and quantizing an analog audio signal.

Since the signal interpolating device of this invention is constructedas above, the frequency components essentially contained in the originalsignal (before the particular band components are suppressed) can bereproduced with high fidelity and can be used for interpolating thesuppressed signal. It is therefore possible to recover a signal having agood similarity to the original signal.

In the device of the invention, Fourier transform and inverse transformdealing with a broad band signal and having a high resolution are notnecessarily required to process a main signal itself. Namely, accordingto an approach adopted by the invention, although signal processing isperformed by paying attention to the frequency components of a signal,it is not necessarily required to incorporate a process of converting amain signal from a “time domain” to a “frequency domain” (or converselyconverting a main signal from the “frequency domain” to the “timedomain”).

According to the invention, the look-up table for searching aninterpolation signal level on the basis of a spectrum pattern is formedby using a large number of input signal samples. It is thereforepossible to select a proper interpolation signal level at a highprecision and perform a frequency interpolation process at a highprecision. According to another aspect of the invention, the look-uptable is formed by reflecting the auditory test results of testlisteners by using specific reproduction means, so that a very naturalreproduction sound quality in terms of auditory senses can be obtained.

As described above, in the frequency interpolating device of theinvention, a large physical amount is analyzed in a long time for eachsignal spectrum, and the look-up table is used which stores dataconfigured in advance by auditory tests of acoustic signals by testlisteners. Using the look-up table can therefore simplify the devicecircuit structure considerably. Accordingly, the frequency interpolatingdevice of the invention can realize all computation processes necessaryfor digital signal processing only by a one-chip audio DSP so that ithas a very high practical value.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual diagram illustrating a basic function of theinvention.

FIG. 2 is a block diagram showing the fundamental structure of afrequency interpolating device of the invention.

FIG. 3 is a diagram showing an example of an interpolating signalgeneration unit as a main constituent element of the device shown inFIG. 2.

FIG. 4 is a diagram showing an example of the structure of a frequencyanalyzing unit as a main constituent element of the device shown in FIG.2.

FIG. 5 is a diagram showing a spectrum pattern represented bydistribution of N-order vectors.

FIG. 6 is a flow chart illustrating a series of processes of comparingan input spectrum pattern with a reference spectrum pattern.

FIG. 7 is a diagram showing an example of a list to be used for creatinga look-up table indicating a correspondence between a reference spectrumpattern and a corresponding interpolation level.

FIG. 8 is a diagram illustrating a simplified method of searching aninterpolation level according to an embodiment of the invention.

FIG. 9 is a diagram illustrating a simplified method of searching aninterpolation level according to another an embodiment of the invention.

FIG. 10 is a diagram illustrating a simplified method of searching aninterpolation level according to still another an embodiment of theinvention.

EMBODIMENTS OF THE INVENTION

With reference to the accompanying drawings, embodiments of a frequencyinterpolating device and method of the invention will be described indetail.

FIG. 1 is a diagram showing a simplified fundamental function of thefrequency interpolating device of the invention. In the fundamentaloperation of the frequency interpolating device of the invention, asignal 1 is input which has suppressed frequency components in aparticular frequency band. The frequency components in the suppressedband to be interpolated are created from the input signal 1, and thecreated signal (interpolation signal) 2 (at a predetermined level) isadded to (interpolated into) the input signal 1 to obtain an outputsignal 3 (which is an approximate signal recovered from the originalsignal). The level (hereinafter called an interpolation level) of theinterpolation signal 2 to be added to (interpolated into) the inputsignal 1 is adjusted by a variable attenuator 4. The level adjustment bythe attenuator 4 is controlled in accordance with the frequency analysisresult of the input signal (by a frequency analyzer 7) 1 (or morespecifically, in accordance with short time frequency spectruminformation of the input signal). The short time spectrum of the inputsignal 1 changes from time to time. The device of the invention respondsto such a change from time to time (dynamic response) and selects an(adaptive) interpolation level suitable for each spectrum pattern. Inthis context, it can be said that the device of the invention shown inFIG. 1 constitutes a dynamic adaptive system.

FIG. 2 is a block diagram showing a more concrete structure of thefrequency interpolating device of the invention. As shown, the device ofthe invention is constituted mainly of an interpolation signalgenerating unit 20, a frequency analyzing unit 21, an interpolationlevel generating unit (constituted of a reference spectrum generator 22and a spectrum comparator 23) 24, a level adjusting unit 25, an addingunit 26 and a delay unit 27.

In this invention, an input signal a to be frequency-interpolated (by aremoved particular frequency band) is input to the interpolation signalgenerating unit 20 for generating a suppressed band component signal(interpolation signal) to thereby create an interpolation signal b. Theinput signal a is also input to the frequency analyzing unit 21 tocreate a signal c representative of the spectrum of the input signal.The created spectrum signal c is patterned and compared with eachreference spectrum pattern registered in advance in the referencespectrum generating unit 22. An interpolation level coefficient g isoutput which indicates the interpolation level corresponding to theassociated reference pattern, and supplied to the level adjusting unit25. The level adjusting unit 25 adjusts the interpolation signal boutput from the interpolation signal generating unit 20 to obtain aproper level matching the interpolation level coefficient g, andsupplies the adjusted level to the adding unit 26 to be added to theinput signal. A recovered signal after interpolation is thus output fromthe output terminal. The delay unit 27 delays the input signal by apredetermined time in order to compensate for the signal processing timetaken for the spectrum pattern comparison. If a signal analysis windowtime width is relatively long or if the comparison process is performedat high speed, this delay unit 27 is not always required.

The particular structure of each constituent element described abovewill be described sequentially. FIG. 3 shows an example of the structureof the interpolation signal generating unit 20 constituted of aband-pass filter 30, an oscillator 31, a mixer 32 and a low-pass filter33. The band-pass filter 30 derives from an input signal a frequencycomponent signal (e.g., a signal having a center frequency fc andfrequency components in a bandwidth Δf) to be used for interpolation.This derived band component signal a₁ is mixed with (multiplied by) asine wave signal sin(2πfgt) created by the oscillator 31, at the mixer32 to thereby create a synthesized signal a₂ of two signals having thebandwidth Δf and center frequencies (f_(g)+f_(c)) and (f_(g)−f_(c)). Thesynthesized signal a₂ is passed through the low-pass filter 33 to obtainonly the signal having the center frequency of (f_(g)−f_(c)). If thefrequency (f_(g)−f_(c)) is set to a center frequency f_(int) of thesuppressed frequency band, a signal in the remaining frequency band(f_(c,) Δf) of the input signal a can be frequency converted into asignal in the interpolation band (f_(int,) Δf). It is therefore possibleto create a desired interpolation signal for interpolating thesuppressed band. In generating the desired interpolation signal, it isobvious that Fourier transform and inverse Fourier transform can beused.

FIG. 4 shows an example of the structure of the frequency analyzing unit21 constituted of a plurality of pairs (N) of a band-pass filter 40 andan effective value circuit (RMS) 45. With this circuit configuration, aband to be frequency analyzed is divided into N division bands (F₁, F₂,F₃, . . . , F_(N)), and an effective value d_(i) (i=1, 2, . . . , N) ofthe frequency components in each division band is calculated. It isobvious to adopt a method of obtaining a complex frequency vectorR(ω)+jI(ω) and calculating {R²(ω)+I²(ω)}^(1/2) by using a Fourieranalyzer.

The reference spectrum generator 22 uses a read-only memory (ROM)storing data of spectrum patterns calculated beforehand (a set ofamplitude effective values in each division frequency band).

A spectrum pattern represented by effective values in each division bandobtained by N-dividing the frequency band to be analyzed can beexpressed by a vector having the respective effective values d_(i) (i=1,2, 3, . . . , N) as its components. Namely, the spectrum pattern can beexpressed by:

ti F _(j)=(d _(1j) , d _(2j) , d _(3j) , d _(4j) , . . . , d _(Nj))

An optional frequency spectrum pattern (FIG. 4(a)) obtained by passing agiven signal through the frequency analyzing unit 21 in a predeterminedtime window (e.g., such as shown in FIG. 4(b)) can be represented byN-order vectors disposed in an N-order coordinate space (F₁, F₂, . . . ,F_(N)). If all spectrum patterns of a given signal, i.e., vectorsF_(j)=(d_(1j), d_(2j), d_(3j), d_(4j), . . . , d_(Nj)) are disposed inthe N-order space, these vectors are not distributed uniformly but theyare distributed as clusters as shown in FIG. 5. It is therefore possibleto calculate a representative vector Fk^((R)) of each cluster. Accordingto this invention, such a representative vector F_(k) ^((R))=(d_(1j)^((R)), d_(2k) ^((R)), . . . , d_(Nk) ^((R))) is calculated for manysamples of an input spectrum collected beforehand, and the calculatedvector is stored in the reference vector generating ROM as the referencevector data.

Next, the structure of the spectrum comparator 23 will be described. Thespectrum comparator 23 judges whether which one of a finite number ofreference spectrum patterns, i.e., reference vectors F_(k)^((R))(R)=(d_(1k) ^((R)), d_(2k) ^((R)), . . . , d_(Nk) ^((R))) (k=1, .. . , M), corresponds to the input spectrum pattern, i.e., an optionalinput vector F_(j)=(d_(1j), d_(2j), . . . , d_(Nj)) (j=1, . . . , N) (inother words, judges which one belongs to which cluster). Morespecifically, from the viewpoint of which one of the reference vectorsF_(k) ^((R)) is nearest to the input vector F_(j), distances arecalculated between the given input vector F_(j) (input vector pattern)and all the reference vectors F_(k) ^((R)) (reference spectrum patterns)to select the reference vector (spectrum pattern) having the longestinter-vector distance δ_(jk) (i.e., most similar spectrum pattern). Thisprocedure is illustrated in the flow chart of FIG. 6 showing a sequenceof processes for finding the reference vector F_(k) ^((R)) to which thegiven input vector F_(j) belongs. As illustrated in this flow chart,after it is judged which one of the prepared reference spectrum patternF_(k) ^((R)) (k=1, . . . , M) belongs to the input spectrum patternF_(j), an interpolation level coefficient (as an index for designatingthe interpolation level) g corresponding to the judged referencespectrum pattern F_(k)(R) is output.

In this case, there is an issue that what interpolation level isassigned to each reference spectrum pattern F_(k) ^((R)). This issue isthe core of the invention in some sense.

It is assumed in this invention that a preset reference spectrum patternand a corresponding interpolation level (regarding a relative level atwhich the interpolation signal is added to an input signal) aredetermined from the following two methods.

(1) Method Using Auditory Test

-   (1) Acoustic signal samples are collected which are used as    references of audio signals (over a number of spectrum patterns)    whose particular bands were suppressed.-   (ii) A predetermined number of test listeners (having a capability    of distinguishing between musical tone qualities) are made to listen    to sample sounds under a reference facility and environment to make    them judge whether the sound quality and balance in each band are    sufficient or not.-   (iii) If it is judged insufficient, the test listeners are made to    manually move, for example, the variable equalizer such as shown in    FIG. 1 to adjust the acoustic signal level.-   (iv) While the test listeners are made adjust the volume in the    suppressed sound band of each acoustic signal sample for each of a    number of spectrum patterns, adjustment levels are collected as    interpolation level data. For example, the adjustment level may be    “0” (addition of an interpolation signal is unnecessary), “1” (an    interpolation signal at its level is added to an input signal),    “0.5” (an interpolation signal at its half level is added, “0.25”    (an interpolation signal at its ¼ level is added) and the like.-   (v) In accordance with the collected interpolation level data, a    list is formed representing a correspondence between a reference    vector pattern and an interpolation level value, and a reference    look-up table (ROM) is created based upon the list.-   (vi) If the reference table is required to be changed due to the    environment and conditions realized by the reproducing means, a    suitable test listener is prepared, and if necessary, specific    samples are prepared, to perform fine adjustment in the manner    similar to that described above in accordance with the reference    table and create the reference look-up table (ROM).

(2) Method Using Frequency Analysis

-   (1) A number of audio signal samples whose particular bands were    suppressed are collected and classified into a plurality of spectrum    patterns by physical spectrum analysis.-   (ii) The correspondence between each classified spectrum pattern and    a level of the original sound (before suppression) in a particular    suppressed band is analyzed to create a list representative of a    correspondence between each spectrum pattern and a level value in    the suppressed band which was contained essentially in the original    sound.-   (iii) In accordance with this correspondence list between the    spectrum and interpolation level, a look-up table (ROM) is formed    which represents a correspondence between a reference spectrum    pattern and an interpolation level value.

FIG. 7 shows an example of a correspondence list between the referencespectrum pattern and interpolation level obtained by the methoddescribed above. The contents of this list stored in the referencespectrum pattern ROM include each memory address and correspondingstorage data.

Description has been made on a general method of determining aninterpolation level by obtaining input spectrum patterns throughspectrum analysis of input signals and classifying the patterns intoreference spectrum patterns. Next, description will be given for amethod of performing more simply the above sequence of operations(frequency analysis→spectrum pattern calculation→interpolation leveldetermination).

In a method illustrated in FIG. 8, an input spectrum pattern is madediscrete and binarized, and by using this binarized data as an addressof ROM, the interpolation level coefficient g is obtained as the memorycontents. With this method, an input spectrum pattern (d_(1j), d_(2j), .. . , d_(nj)) is obtained by using the above-described structure (e.g.,the frequency analyzing unit shown in FIG. 4). The effective valued_(ij) (i=1, 2, 2, . . . , N) in each band is normalized, made discrete(e.g., octal values: 1, 2, 3, . . . , N) and binarized. It is assumedfor example that an input spectrum pattern F_(j) in five division bandsis given by F_(j)=(0.63, 0.80, 0.43, 0.5, 0.2). This pattern is dividedby an ensemble average in each band and made discrete to obtain adiscrete spectrum (5, 6, 3, 7, 4). This spectrum is binarized to obtain(101, 110, 011, 111, 100). By using this binary data as address data, itis directly supplied to the memory. This memory stores in advance aninterpolation level coefficient (g) corresponding to the binaryrepresentation of a spectrum pattern. As the spectrum code is suppliedto the memory, the interpolation level coefficient (g) can be obtainedimmediately as a memory output.

The input spectrum pattern (d_(1j), d_(2j), . . . , d_(nj)) may bedirectly converted into a binarized spectrum which is used as a memoryaddress. For example, this binarization is performed on the basis ofwhether the level d_(ij) (i=1, 2, 2, . . . , N) is either not smallerthan or smaller than the ensemble average in each band. For example, inthe above example of the input spectrum pattern F_(j):(0.63, 0.80, 0.43,0.5, 0.2), if the ensemble average is given by (0.7, 0.6, 0.5, 0.4, 0.2,0.01), then a binary spectrum pattern (0, 1, 0, 1, 0) can be obtained.

Similar to the above example, each interpolation coefficient gcorresponding to the binary representation is stored in the referencespectrum memory. If the binary spectrum pattern data is directlysupplied to the address terminal of the memory, the interpolation levelcoefficient can be obtained as a memory output. In the example shown inFIG. 8(b), a spectrum pattern is binarized to obtain data (1, 0, 1, 1,0) which is supplied to the memory as a memory address to obtain aninterpolation level coefficient g=1.0.

As shown in FIG. 9, attention is paid to two specific frequencies(angular frequencies ω₁ and ω₂) of an input signal. Interpolation levelcoefficients (0 to 1) corresponding to spectra each classified by a pairof amplitude levels (α, β) at the frequencies are stored beforehand in amemory in a matrix shape. Frequency analysis of the two frequencies ω₁,ω₂ is performed by calculating complex Fourier components R and I shownin FIG. 9. A component level α at the first frequency (angular frequencyω₁) and a component level β at the second frequency (angular frequencyω₂) are obtained and an interpolation level coefficient g correspondingto (α, β) can be read from the memory.

Lastly, in the simplest method illustrated in FIG. 10, only one operatorfor obtaining a complex Fourier coefficient is used. The real part (R)and imaginary part (I) of output Fourier components are related to aspectrum pattern. With this method, the interpolation level coefficientis read from the memory in accordance with paired data of the real andimaginary parts (R, I). In the example shown in FIG. 10, the memorylocation is determined directly from the outputs (α, β)=(α_(m), β_(n))and the value g_(mn) is read. Although a precision of similarity to aspectrum pattern is not so good, this method is effective for the casethat there is a remaining frequency band (e.g., ω₁) having a strongcorrelation with the level in the suppressed frequency band. This methodis particularly useful in that the circuit structure can be simplified.

INDUSTRIAL APPLICABILITY

It is possible to recover at a good similarity the high frequencycomponents of an audio signal or the like whose high frequencycomponents were suppressed and to synthesize a acoustic signal similarto an original signal. It is therefore possible to reproduce an audiosignal having a high quality and a sufficiently broadened high frequencyband. According to the techniques of this invention, auditory testresult data of an audio signal or the like by test listeners can bereflected upon the device structure so that a very natural reproductionsound quality can be obtained. Since the calculation amount necessaryfor frequency interpolation digital signal processing is relativelysmall, the device of a small scale can be used and the cost can bereduced considerably.

1. A frequency interpolating device for receiving an input signal havinga suppressed frequency component in a particular frequency band of anoriginal signal and recovering a signal similar to the original signalby approximately creating the suppressed frequency component, whereinwhen a frequency component in the suppressed band created from the inputsignal is added to the input signal, an addition level of the frequencycomponent to be added is adaptively set on the basis of a spectrumpattern of remaining frequency components of the input signal.
 2. Thefrequency interpolating device according to claim 1, wherein settingsaid addition level is performed by using a look-up table storing datarepresentative of a correspondence between a plurality of referencefrequency spectrum patterns and predetermined addition levels.
 3. Thefrequency interpolating device according to claim 2, wherein the datastored in said look-up table is created on the basis an auditory testresult made on a plurality of acoustic signal samples.
 4. The frequencyinterpolating device according to claim 2, wherein the data stored insaid look-up table is created on the basis of a frequency analysisresult of a plurality of acoustic signal samples.
 5. A frequencyinterpolating device for receiving an input signal having a suppressedfrequency component in a particular frequency band of an original signaland recovering a signal similar to the original signal by approximatelycreating the suppressed frequency component, the frequency interpolatingdevice comprising: means for creating an interpolation signal having afrequency component in said suppressed band, from said input signal;means for spectrum-analyzing said input signal to derive a spectrumpattern; comparing means for comparing said derived spectrum patternwith a plurality of reference spectrum patterns registered beforehand,and on the basis of a comparison result to select an addition level ofsaid created interpolation signal relative to said input signal; andmeans for adding said created interpolation signal to said input signalat said selected addition level.
 6. The frequency interpolating deviceaccording to claim 5, wherein said comparing means includes a look-updata table storing data representative of a correspondence between saidreference spectrum patterns and said addition levels, said look-up datatable being created on the basis of an auditory test of a plurality ofacoustic signal samples.
 7. The frequency interpolating device accordingto claim 5, wherein said means for deriving the spectrum pattern of saidinput signal operates to output a code corresponding to said derivedspectrum pattern, and said comparing means is made of a memory thatstores data representative of a correspondence between said referencespectrum patterns and said addition levels, and wherein said code isinputted to said memory as a memory address to output the addition levelstored at a memory location indicated by the memory address designatedby said code.
 8. The frequency interpolating device according to any oneof claims 1 to 7, wherein said input signal is a digital audio signalobtained by sampling and quantizing an analog audio signal.
 9. Thefrequency interpolating method of receiving a suppressed frequencycomponent in a particular frequency band of an original signal andrecovering a signal similar to the original signal by approximatelycreating the suppressed frequency component, wherein: when a frequencycomponent in the suppressed band created from the input signal is addedto the input signal, an addition level of the frequency component to beadded is adaptively set on the basis of a spectrum pattern of remainingfrequency components of the input signal.
 10. The frequencyinterpolating method according to claim 9, wherein setting said additionlevel is performed by using a look-up table storing data representativeof a correspondence between a plurality of reference frequency spectrumpatterns and predetermined addition levels.
 11. The frequencyinterpolating method according to claim 10, wherein the data stored insaid look-up table is created on the basis of an auditory test result ofa plurality of acoustic signal samples.
 12. A frequency interpolatingmethod for receiving an input signal having a suppressed frequencycomponent in a particular frequency band of an original signal andrecovering a signal similar to the original signal by approximatelycreating the suppressed frequency component, said method comprising thesteps of: creating an interpolation signal having a frequency componentin said suppressed band, from said input signal; spectrum-analyzing saidinput signal to derive a spectrum pattern; comparing said derivedspectrum pattern with a plurality of reference spectrum patternsregistered beforehand advance, and on the basis of a comparison result,selecting an addition level of said created interpolation signalrelative to said input signal; and adding said created interpolationsignal to said input signal at said selected addition level.
 13. Thefrequency interpolating method according to claim 12, wherein saidcomparing step searches a look-up data table storing data representativeof a correspondence between said reference spectrum patterns and saidaddition levels, said look-up data table being created on the basis ofan auditory test of a plurality of acoustic signal samples.
 14. Thefrequency interpolating method according to claim 12, wherein said stepof deriving the spectrum pattern of said input signal outputs a codecorresponding to said derived spectrum pattern, and said comparing stepinputs as a memory address said code to a memory that stores datarepresentative of a correspondence between said reference spectrumpatterns and said addition levels, and outputting the addition levelstored at a memory location indicated by the memory address designatedby said code.